基于大数据技术的分布式发电电能质量分析OA

In the context of the continuous advancement of big data technology and digital grid construction,the intelligent operation of the power grid faces both challenges and opportunities.To fully utilize the vast amount of data accumulated during power system operation,a new big data analysis and mining strategy was proposed in this study.Based on actual operational data from the power system,a big data analysis algorithm and visualization model were developed to conduct multidimensional statistical analysis from the perspectives of fault type and time scale,aiming to understand the operational status of distributed generation grids and the patterns of power quality faults,while further exploring their fault mechanisms.The research results showed that the proposed big data analysis and mining strategy effectively leveraged actual power system operational data,providing an intuitive understanding and analysis of power grid operational patterns and power quality fault characteristics,thereby offering strong technical support for the intelligent operation of distributed generation and high-quality power supply.